(1) Field of the Invention
The present invention relates to signal processing and more particularly to an apparatus and method for discriminating against non-Gaussian noise contamination of acoustic signals or the like thereby improving detection and estimation thereof.
(2) Description of the Prior Art
Signal processors generally must separate the signal from the broadband noise in which it is additively embedded. Traditional and currently used methods for detection and estimation of such noise contaminated signals either assume that the underlying noise environment is Gaussian or else the noise is not considered in the technique. For example, the estimated noise spectrum may be used to detect narrow-band signals, which technique is near optimum if the noise is Gaussian. However, if the noise is non-Gaussian then such a technique is not optimum and performance is significantly degraded. What is needed is a signal processor which can discrimate against non-Gaussian noise thereby increasing the signal-to-noise ratio.
A previous processing technique that is important to this invention uses a discrete Fourier transform (DFT) or a fast Fourier transform (FFT) to extract narrowband frequency domain signal components. Such a technique is also employed in the present invention.